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An Experimental Analysis of Clustering Sentiments for Opinion Mining

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Published:13 January 2017Publication History

ABSTRACT

Social Media Analytics playing a major role in e-commerce for extracting the useful information of a product/service. Opinion Mining has become the key process of Social Media Analytics. In this paper, the process of opinion mining in social media while dealing with different kind of opinionated documents and the challenges associated to opinion mining from social media has been discussed. The twitter is a big online social activity where some millions of people share their opinions. Applying sentiment analysis on social media data to get product reviews based on the product features is one major concern. K-means clustering technique applied on a sample twitter dataset to cluster different sentiments in context with different features of products and been evaluated and explained with the help of a machine learning tool.

References

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  • Published in

    cover image ACM Other conferences
    ICMLSC '17: Proceedings of the 2017 International Conference on Machine Learning and Soft Computing
    January 2017
    233 pages
    ISBN:9781450348287
    DOI:10.1145/3036290

    Copyright © 2017 ACM

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 13 January 2017

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